Automatic train regulation for metro lines using dual heuristic dynamic programming

Abstract

Issues regarding capacity and service quality of metro lines have been receiving attention in worldwide transportation circles recently. Because investment in metro infrastructure is costly, increasing capacity utilization of existing systems while maintaining service quality, particularly in environments where disturbance occurs frequently, is a challenge. For highly homogeneous railway systems such as metro lines, the robustness of the train regulation system against disturbances is an important factor affecting capacity utilization and service quality. Train regulation in metro lines is essentially a highly non-linear, stochastic, and constrained optimization problem. This article proposes an automatic train regulation (ATR) design using dual heuristic dynamic programming (DHP). The ATR system makes easier the handling of the non-linear and stochastic characteristics of metro line with infrastructure constraint; and near-optimal regulation can be obtained more rapidly and accurately. The verification of the DHP-based ATR referring to practical operation data of Taipei metro is presented, and a comparison with a design using linear quadratic regulator is also provided, especially regarding robustness against disturbance.